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Learning fast and slow: deviations from the matching law can reflect an optimal strategy under uncertainty
Kiyohito Iigaya, Yashar Ahmadian, Leo P. Sugrue, Greg S. Corrado, Yonatan Loewenstein, William T. Newsome, Stefano Fusi
doi: https://doi.org/10.1101/141309
Kiyohito Iigaya
1Center for Theoretical Neuroscience, College of Physicians and Surgeons, Columbia University, New York, NY 10032, USA
2Gatsby Computational Neuroscience Unit, UCL, London W1T 4JG, UK
3Department of Physics, Columbia University, New York NY 10027
4Max Planck UCL Centre for Computational Psychiatry and Ageing Research, London WC1B 5EH, UK
Yashar Ahmadian
1Center for Theoretical Neuroscience, College of Physicians and Surgeons, Columbia University, New York, NY 10032, USA
5Institute of Neuroscience Departments of Biology and Mathematics University of Oregon, Eugene, OR 97403
Leo P. Sugrue
6Howard Hughes Medical Institute and Department of Neurobiology, Stanford University School of Medicine, Stanford, CA 94305
7Neuroradiology Section, Department of Radiology and Biomedical Imaging, Universtiy of California, San Francisco, CA 94143
Greg S. Corrado
6Howard Hughes Medical Institute and Department of Neurobiology, Stanford University School of Medicine, Stanford, CA 94305
8Google Inc., CA
Yonatan Loewenstein
9Department of Neurobiology, Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem 91904, Israel
William T. Newsome
6Howard Hughes Medical Institute and Department of Neurobiology, Stanford University School of Medicine, Stanford, CA 94305
Stefano Fusi
1Center for Theoretical Neuroscience, College of Physicians and Surgeons, Columbia University, New York, NY 10032, USA
10Mortimer B. Zuckerman Mind Brain Behavior Institute, College of Physicians and Surgeons, Columbia University, New York, New York, USA
11Kavli Institute for Brain Sciences, Columbia University, New York, New York, USA
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Posted May 25, 2017.
Learning fast and slow: deviations from the matching law can reflect an optimal strategy under uncertainty
Kiyohito Iigaya, Yashar Ahmadian, Leo P. Sugrue, Greg S. Corrado, Yonatan Loewenstein, William T. Newsome, Stefano Fusi
bioRxiv 141309; doi: https://doi.org/10.1101/141309
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